Update rank limits for SLICE, TILE and TRANSPOSE

Updated to align with corresponding changes to the
spec.

In addition, some ERROR_IF tests have been updated to
match the checks specified by the spec, including:
PAD, SLICE, TILE, TRANSPOSE.

Signed-off-by: Luke Hutton <luke.hutton@arm.com>
Change-Id: Ie2c5f48e79a5610eb82739170e25057a63dac1d8

4 files changed, 58 insertions, 18 deletions

diff --git a/verif/generator/tosa_arg_gen.py b/verif/generator/tosa_arg_gen.py
index 75ca634..9209d9c 100644
--- a/verif/generator/tosa_arg_gen.py
+++ b/verif/generator/tosa_arg_gen.py
@@ -176,6 +176,7 @@ class TosaTensorGen:
         for i in range(pl + const):
             shape_list.append(shape.copy())
 
+            # Generates an input rank mismatch for operators with more than one input
             if error_name == ErrorIf.RankMismatch:
                 if rank == 1 and i != 1:
                     shape = testGen.makeShape(rank + testGen.rng.choice([1, 2, 3]))
diff --git a/verif/generator/tosa_error_if.py b/verif/generator/tosa_error_if.py
index ee227b3..b19d5e9 100644
--- a/verif/generator/tosa_error_if.py
+++ b/verif/generator/tosa_error_if.py
@@ -1067,7 +1067,9 @@ class TosaErrorValidator:
 
         if check:
             input1_shape = kwargs["input1"].shape
-            input2_shape = kwargs["input2"].shape
+            input2_shape = (
+                kwargs["input2"].shape if "input2" in kwargs else input1_shape
+            )
             # In case of SELECT op
             input3_shape = (
                 kwargs["input3"].shape if "input3" in kwargs else input2_shape
@@ -1921,11 +1923,13 @@ class TosaErrorValidator:
             input_shape = kwargs["input_shape"]
             output_shape = kwargs["output_shape"]
             size = kwargs["size"]
-            rank = len(input_shape)
-            if len(size) == rank:
-                for index in range(rank):
-                    if size[index] != output_shape[index]:
-                        error_result = True
+
+            if len(input_shape) == len(output_shape):
+                rank = len(input_shape)
+                if len(size) == rank:
+                    for index in range(rank):
+                        if size[index] != output_shape[index]:
+                            error_result = True
 
         info_dict = {
             "error_name": error_name,
diff --git a/verif/generator/tosa_test_gen.py b/verif/generator/tosa_test_gen.py
index a768da0..7fef942 100644
--- a/verif/generator/tosa_test_gen.py
+++ b/verif/generator/tosa_test_gen.py
@@ -14,6 +14,7 @@ from generator.tosa_error_if import TosaErrorIfArgGen
 from generator.tosa_error_if import TosaErrorValidator
 from generator.tosa_error_if import TosaInvalidValidator
 from generator.tosa_utils import DTYPE_ATTRIBUTES
+from generator.tosa_utils import get_rank_mismatch_shape
 from generator.tosa_utils import get_wrong_output_type
 from generator.tosa_utils import MAX_RESIZE_DIMENSION
 from generator.tosa_utils import usableDTypes
@@ -1263,6 +1264,7 @@ class TosaTestGen:
             input_list=input_list,
             output_list=output_list,
             num_operands=num_operands,
+            input1=a,
         ):
             return None
 
@@ -1369,6 +1371,7 @@ class TosaTestGen:
             input_list=input_list,
             output_list=output_list,
             num_operands=num_operands,
+            input1=a,
         ):
             return None
 
@@ -1404,6 +1407,7 @@ class TosaTestGen:
             input_list=input_list,
             output_list=output_list,
             num_operands=num_operands,
+            input1=a,
         ):
             return None
 
@@ -1438,6 +1442,7 @@ class TosaTestGen:
             input_list=input_list,
             output_list=output_list,
             num_operands=num_operands,
+            input1=a,
         ):
             return None
 
@@ -3657,6 +3662,8 @@ class TosaTestGen:
                 TosaErrorValidator.evWrongOutputType,
                 TosaErrorValidator.evWrongInputList,
                 TosaErrorValidator.evWrongOutputList,
+                TosaErrorValidator.evRankMismatch,
+                TosaErrorValidator.evWrongRank,
             ),
         },
         "reshape": {
@@ -3699,7 +3706,7 @@ class TosaTestGen:
         "slice": {
             "op": Op.SLICE,
             "operands": (1, 0),
-            "rank": (1, 4),
+            "rank": (1, 6),
             "build_fcn": (
                 build_slice,
                 TosaTensorGen.tgBasic,
@@ -3718,11 +3725,13 @@ class TosaTestGen:
                 TosaErrorValidator.evWrongOutputType,
                 TosaErrorValidator.evWrongInputList,
                 TosaErrorValidator.evWrongOutputList,
+                TosaErrorValidator.evRankMismatch,
             ),
         },
         "tile": {
             "op": Op.TILE,
             "operands": (1, 0),
+            "rank": (1, 6),
             "build_fcn": (
                 build_tile,
                 TosaTensorGen.tgBasic,
@@ -3735,12 +3744,14 @@ class TosaTestGen:
                 TosaErrorValidator.evWrongOutputType,
                 TosaErrorValidator.evWrongInputList,
                 TosaErrorValidator.evWrongOutputList,
+                TosaErrorValidator.evRankMismatch,
+                TosaErrorValidator.evWrongRank,
             ),
         },
         "transpose": {
             "op": Op.TRANSPOSE,
             "operands": (1, 0),
-            "rank": (1, 4),
+            "rank": (1, 6),
             "build_fcn": (
                 build_transpose,
                 TosaTensorGen.tgBasic,
@@ -3755,6 +3766,9 @@ class TosaTestGen:
                 TosaErrorValidator.evWrongOutputType,
                 TosaErrorValidator.evWrongInputList,
                 TosaErrorValidator.evWrongOutputList,
+                TosaErrorValidator.evWrongRank,
+                TosaErrorValidator.evRankMismatch,
+                TosaErrorValidator.evTensorSizeInputOutputMismatch,
             ),
         },
         # Data nodes
@@ -4539,6 +4553,8 @@ class OutputShaper:
         if error_name == ErrorIf.PadOutputShapeMismatch:
             bad_dim = rng.choice(range(len(output_shape)))
             output_shape[bad_dim] -= rng.choice([1, 2])
+        elif error_name == ErrorIf.RankMismatch:
+            output_shape = get_rank_mismatch_shape(rng, output_shape)
 
         if error_name == ErrorIf.WrongOutputType:
             all_dtypes = [
@@ -4583,7 +4599,7 @@ class OutputShaper:
         return ser.addOutput(output_shape, outputDType)
 
     @staticmethod
-    def sliceOp(ser, rng, a, start, size, error_name=None):
+    def sliceOp(ser, rng, input, start, size, error_name=None):
 
         if error_name == ErrorIf.WrongOutputType:
             all_dtypes = [
@@ -4595,13 +4611,13 @@ class OutputShaper:
                 DType.FP16,
                 DType.BF16,
             ]
-            wrong_dtypes = list(set(all_dtypes) - set([a.dtype]))
+            wrong_dtypes = list(set(all_dtypes) - set([input.dtype]))
             outputDType = rng.choice(wrong_dtypes)
         else:
-            outputDType = a.dtype
+            outputDType = input.dtype
 
+        output_shape = size.copy()
         if error_name == ErrorIf.SizeOutputShapeMismatch:
-            output_shape = size.copy()
             for index in range(len(output_shape)):
                 if output_shape[index] <= 2:
                     output_shape[index] = output_shape[index] + rng.choice([1, 2])
@@ -4609,8 +4625,10 @@ class OutputShaper:
                     output_shape[index] = output_shape[index] + rng.choice(
                         [-2, -1, 1, 2]
                     )
-        else:
-            output_shape = size.copy()
+        elif error_name == ErrorIf.InputSizeStartLengthMismatch:
+            output_shape = input.shape.copy()
+        elif error_name == ErrorIf.RankMismatch:
+            output_shape = get_rank_mismatch_shape(rng, output_shape)
 
         return ser.addOutput(output_shape, outputDType)
 
@@ -4623,6 +4641,9 @@ class OutputShaper:
         for i in range(len(output_shape)):
             output_shape[i] = a.shape[i] * multiples[i]
 
+        if error_name == ErrorIf.RankMismatch:
+            output_shape = get_rank_mismatch_shape(rng, output_shape)
+
         if error_name == ErrorIf.WrongOutputType:
             all_dtypes = [
                 DType.INT8,
@@ -4646,13 +4667,16 @@ class OutputShaper:
 
         assert len(perms) == len(output_shape)
 
-        if error_name == ErrorIf.IndexOutsideBounds:
-            for i in range(len(output_shape)):
-                output_shape[i] = a.shape[0]
-        else:
+        if error_name not in [ErrorIf.IndexOutsideBounds, ErrorIf.IndexUsedTwice]:
             for i in range(len(output_shape)):
                 output_shape[i] = a.shape[perms[i]]
 
+        if error_name == ErrorIf.TensorSizeInputOutputMismatch:
+            for i in range(len(output_shape)):
+                output_shape[i] += rng.integers(1, 10)
+        elif error_name == ErrorIf.RankMismatch:
+            output_shape = get_rank_mismatch_shape(rng, output_shape)
+
         if error_name == ErrorIf.WrongOutputType:
             all_dtypes = [
                 DType.INT8,
diff --git a/verif/generator/tosa_utils.py b/verif/generator/tosa_utils.py
index 29ae898..8ff62f1 100644
--- a/verif/generator/tosa_utils.py
+++ b/verif/generator/tosa_utils.py
@@ -148,6 +148,17 @@ def get_wrong_output_type(op_name, rng, input_dtype):
     return rng.choice(a=incorrect_types)
 
 
+def get_rank_mismatch_shape(rng, output_shape):
+    """
+    Extends the rank of the provided output_shape by
+    an arbitrary amount but ensures the total element
+    count remains the same.
+    """
+    rank_modifier = rng.choice([1, 2, 3])
+    output_shape += [1] * rank_modifier
+    return output_shape
+
+
 def float32_is_valid_bfloat16(f):
     """Return True if float value is valid bfloat16."""
     f32_bits = get_float32_bitstring(f)